Introduction
Suspended particulate matter in the atmosphere plays a key role in Earth's climate. Atmospheric aerosol particles affect the amount of solar radiation absorbed by the Earth system. This is accomplished either when atmospheric aerosol particles directly absorb or scatter incoming solar energy (causing warming or cooling) or when particles act as cloud condensation or ice nuclei (leading to an increase in cloud albedo, which causes cooling). A substantial fraction of particle number and mass across a wide range of environmental conditions arises from sulfur emissions (Clarke et al., 1998; Turco et al., 1982).
Sulfur in Earth's atmosphere in turn originates from natural phenomena like volcanic eruptions and biota decomposition. Violent volcanic eruptions can loft sulfur dioxide (SO to the stratosphere, which can then form sulfur aerosol particles. Those sulfur aerosols can remain suspended in the stratosphere for 1–2 years before falling into the troposphere (Wilson et al., 1993; Deshler, 2008). The three main natural agents for sulfate aerosol formation in troposphere are dimethyl sulfide (DMS), which arises from marine phytoplankton decomposition (Charlson et al., 1987; Kiene, 1999; Simó and Pedrós-Alió, 1999), SO, which occurs naturally as a decay product of plant and animal matter (Grädel and Crutzen, 1994; Hübert, 1999; Capaldo et al., 1999), and carbonyl sulfide (OCS), which is emitted from anaerobic biological activity and provides the main non-volcanic flux of sulfur into the stratosphere (Galloway and Rodhe, 1991; Rhode, 1999).
The atmospheric sulfate burden is substantially perturbed by sulfur emissions associated with anthropogenic activities. The largest anthropogenic source of sulfur is fossil-fuel combustion; coal is the predominant source, but also heavy fuel oil is important (Öm et al., 1996; Smith et al., 2001). Fossil-fuel combustion constitutes two-thirds of the total global sulfur flux to the atmosphere (Rhode, 1999; Wen and Carignan, 2007) and dominates emissions in most populated regions. Other anthropogenic factors also affect the sulfuric acid (HSO budget, notably sulfur aerosol formation in aircraft plumes (Fahey et al., 1995; Curtius et al., 1998), and extensive sulfur use in industry with a direct environmental impact on local scale. However, on a regional to global scale the acidification of fresh water and forest ecosystems is mainly caused by wet and dry deposition of SO and sulfate particles (Simpson et al., 2006).
Sulfur is also a crucial constituent in Venus' atmosphere, an environment with very low relative humidity (RH) (Moroz et al., 1979; Hoffman et al., 1980), forming the main cloud layer in the form of sulfuric acid droplets (Donahue et al., 1982), which are maintained in an intricate photochemical cycle (photooxidation of OCS; Prinn, 1973). Sulfuric acid's reaction paths remain a subject of investigation (Zhang et al., 2010), which makes the study of the sulfur cycle (including the sulfur species SO, SO, SO, HSO an important endeavour for understanding both the chemistry and climate of Venus (Mills et al., 2007; Hashimoto and Abe, 2000).
HSO serves as an effective nucleating species and, thus, strongly influences atmospheric new-particle formation (Laaksonen and Kulmala, 1991; Weber et al., 1999; Kulmala et al., 2000; Yu and Turco, 2001; Fiedler et al., 2005; Kuang et al., 2008). The nucleation rate, which is the formation rate (cm s of new particles at the critical size, strongly depends upon the saturation ratio of HSO. Uncertainty in this ratio results in an uncertainty of several orders of magnitude in the calculated nucleation rate (Roedel, 1979). To model the excess HSO responsible for the gas-to-particle conversion it is necessary to know the vapour pressure of HSO over sulfuric acid and/or neutralised solutions.
The sulfuric acid vapour pressure appears through the free-energy term in the exponent of the new-particle formation rate (Volmer and Weber, 1926; Stauffer, 1976). Quantitative theoretical predictions of nucleation rates are highly uncertain because the pure HSO equilibrium vapour pressure is not well known (Gmitro and Vermeulen, 1964; Doyle, 1961; Kiang and Stauffer, 1973). However, accurate calculations of the HSO vapour pressure require accurate equilibrium rate constant values to constrain the reactions of formation and dissociation of HSO in aqueous solutions.
While HSO is often presumed to be practically non-volatile, this is not always the case. There are several circumstances on Earth and Venus where the vapour pressure of HSO matters: specifically, at very low RH, high temperature (), when there is a deficit of stabilising bases, and when particles are very small. A very important region of Earth's environment is the upper stratosphere, where these conditions prevail (Vaida et al., 2003). Under these conditions HSO can evaporate from particles. This can either inhibit growth of nanoparticles or lead them to shrink.
Furthermore, molecular HSO is never the dominant constituent in sulfuric acid solutions. It will completely dehydrate to sulfur trioxide (SO, which is extremely volatile) in a truly dry system and yet almost entirely dissociate into bisulfate ion (HSO and hydronium cation (HO in the presence of even trace water (HO) (Clegg and Brimblecombe, 1995). This is why HSO is such a powerful desiccant. Also, bases such as ammonia (NH will enhance chemical stabilisation and form sulfate salts. The thermodynamics of the HSO–HO system at low RH are uncertain, so we seek to improve our understanding of this part of the phase diagram. To accomplish this, we measured the shrinkage of nearly pure HSO particles in the CLOUD chamber at CERN at very low RH and then simulated these experiments with an aerosol dynamics model coupled with a thermodynamics model to constrain the equilibrium constants, for the dissociation and the dehydration , of HSO coupling HSO, HSO, and SO. These new values can be used in models that simulate the evolution of sulfate aerosol particles in the atmospheres of Venus and Earth.
Aqueous-phase sulfuric acid reactions
HSO dissociation and potential dehydration to SO are the principal subjects of this study. In aqueous solutions HSO can dissociate in two steps. HSO partially dissociates to form HSO via Reaction (R1). represents the equilibrium constant for Reaction (R1). HSO can then undergo a second dissociation Reaction (R2) to form a sulfate ion (SO. In the above reactions, sulfur's oxidation number is 6 (S(VI)).
For dilute aqueous solutions, Reaction (R1) is considered to be complete. However, when the mole fraction of S(VI) exceeds 0.5, HSO can be detected in the solution (Walrafen et al., 2000; Margarella et al., 2013). When HSO is present in the solution, dehydration of HSO to form SO (Reaction R3) can also be important (Wang et al., 2006; Que et al., 2011). represents the equilibrium constant for Reaction (R3) on a mole fraction basis. NH, which mainly originates from anthropogenic agriculture emissions, is the most abundant base in atmospheric secondary aerosol particles. NH neutralises sulfuric acid particles by reacting with H and forming an ammonium ion (NH (Reaction R4).
Even in the cleanest environments, such as the stratosphere, NH is present at low concentrations and NH will be dissolved in the acidic sulfate particles.
Methods
In the CLOUD (Cosmics Leaving OUtdoor Droplets; Kirkby et al., 2011) chamber at CERN, we measured the HSO aerosol particle evaporation under precisely controlled temperature and relative humidity. We designed experiments to accomplish a gradual decrease in RH (from 11.0 to 0.3 %) under atmospherically relevant conditions. To understand the processes governing the measured particle evaporation, we modelled the experiments with the Aerosol Dynamics, gas- and particle-phase chemistry model for laboratory CHAMber studies (ADCHAM; Roldin et al., 2014).
Experimental setup
Details of the CLOUD chamber, the main element of the experimental setup can be found in Kirkby et al. (2011) and Duplissy et al. (2016). For the experiments described here, we formed and grew sulfuric acid particles in the chamber by oxidising SO with OH radicals that were generated by photolysing O and allowing the resulting O(D) to react with water vapour. During these experiments we fed the aerosol population to an array of instruments for characterisation of both physical and chemical properties.
We utilised the following instruments to measure gas-phase concentrations: a SO monitor (enhanced trace level SO 15 analyser, model 43i-TLE, Thermo Scientific, USA), an O monitor (TEI 49C, Thermo Environmental Instruments, USA) and a chemical ionisation mass spectrometer (CIMS) to measure the gas-phase HSO concentration ([HSO] between 5 10 and 3 10 cm; Kürten et al., 2011, 2012). The CIMS data provided the total gaseous sulfuric acid concentration, [HSO], without constraining the hydration state of the evaporating molecules (e.g. HSO associated with one, two, or three HO molecules).
We measured the evolution of the aerosol number size distribution with a scanning mobility particle sizer (SMPS; Wang and Flagan, 1990), which recorded the dry particle mobility diameter in the size range from about 10 to 220 nm. We operated the SMPS system with a recirculating dried sheath flow (RH 14 % controlled by a silicon dryer) with a sheath to aerosol sample flow ratio of .3 L. We maintained the differential mobility analyser (DMA) and recirculating system at 278–288 K by means of a temperature control rack, while we operated the condensation particle counter (CPC) at room temperature. We corrected the SMPS measurements for charging probability, including the possibility of multiple charges, diffusion losses, and CPC detection efficiency.
We measured aerosol particle chemical composition with an Aerodyne aerosol mass spectrometer (AMS) quantifying sulfate, nitrate, ammonium and organics for particles between 50 and 1000 nm aerodynamic diameter (Jimenez et al., 2003; Drewnick et al., 2006; Canagaratna et al., 2007). The AMS provided the mass concentration measurements (g m calculated from the ion signals by using measured air sample flow rate, nitrate ionisation efficiency (IE) and relative IE of the other species.
The experimental procedure
To study aerosol particle evaporation, the formation of sulfuric acid particles preceded. At the lowest HO levels (RH 11 %) and in the presence of O, controlled UV photo-excitation reactions initiated the oxidation of SO to HSO. Sulfuric acid particles nucleated and grew to a size of 220 nm by condensation of HSO at a quasi-constant gas-phase concentration ( 1 10 cm with an uncertainty of 20 %). The HSO formation and particle growth ended when we closed the shutters in the front of the UV light source. Afterwards, we induced particle shrinkage by decreasing the RH. We decreased the RH in two separate ways; either by minimising the influx of water vapour to the chamber, or by increasing the temperature. This separation in experimental procedures gave the ability to achieve and control extremely low RH values (Table 1).
Summary of the experimental conditions: temperature (), relative humidity (RH), and gaseous sulfuric acid concentration ([HSO]) which is also given as saturation vapour pressure ( for each experiment.
Run No | CLOUD | RH | [HSO], | [HSO], | |||
---|---|---|---|---|---|---|---|
Run No | (K) | (%) | (# cm | (# cm | (Pa) | (Pa) | |
1 | 914.01 | 288.8 | 10.1–0.5 | 6.0 10 | 1.2 10 | 2.3 10 | 5.0 10 |
2 | 914.06 | 288.8 | 3.5–0.5 | 2.3 10 | 1.0 10 | 9.0 10 | 4.2 10 |
3 | 919.02–04 | 268.0–293.0 | 1.4–0.3 | 1.8 10 | 2.0 10 | 6.3 10 | 2.7 10 |
After the end of the particle formation period and during the initial steps of evaporation, before the RH started to decrease, the aerosol size distribution remained nearly constant. Subsequently, the RH decreased gradually initiating the particle evaporation. When the RH reached a certain low value (RH 1.5 % for K) the particles shrank rapidly, as revealed by the SMPS measurements, and the [HSO] increased until it reached a peak value (see Supplement, Fig. S1). The [HSO] was significantly higher than the background concentration before the onset of evaporation (Table 1). After reaching a maximum in gas-phase concentration, the sulfuric acid decreased again, though the size distribution remained stable (e.g. 50 (10) nm for experiments 1 and 2; see Sect. 4.3) depending on the RH and conditions. This behaviour revealed that the remaining aerosol could not be pure sulfuric acid but rather consisted of a more stable chemical mixture that inhibited further evaporation.
Similarly, the AMS recorded the evaporation of particles (see Supplement, Fig. S1). The AMS measurements showed that the particles were composed almost exclusively of sulfuric acid (but not pure HSO. Based on AMS data, calculations of the kappa value (; Petters and Kreidenweis, 2007), which is defined as a parameter that describes the aerosols water uptake and cloud condensation nucleus activity (CCN activity), of the mixed particles as a function of time during particle evaporation (see Supplement, Fig. S2) yield a value close to the for pure sulfuric acid particles (Sullivan et al., 2010). A value is indicative of the solubility of aerosol particles, with referring to an insoluble particle and to pure sulfuric acid particles. is computed by the approximate equation, Eq. (1) when the critical diameter and critical saturation (or supersaturation, , when referring to CCN activity) are known. The term can be calculated from the water properties.
The model framework
In the present work we use ADCHAM (Roldin et al., 2014, 2015) to study the evolution of the particle number size distribution and particle chemical composition. Instead of simulating the new-particle formation in the CLOUD chamber, we use the measured particle number size distribution before the UV lights are turned off as well as time sequences of RH, and [HSO] as inputs to the model (Fig. 1). In order to capture the evolution of the particle number size distribution we consider Brownian coagulation, particle wall deposition, condensation and evaporation of HSO, SO and HO from the particles.
Schematic of the ADCHAM model optimised for the sulfur particle evaporation at low RH.
[Figure omitted. See PDF]
The activity coefficients
Within an aqueous electrolyte solution, such as the HSO–SO–HO system, cations, anions and molecular species all disrupt ideality. Here, we consider interactions between ions (HSO, SO, NH, H and molecules (HSO, SO, HO) in the particle-phase chemistry model. To calculate the molality-based activity coefficients for the inorganic ions ( and the mole-fraction-based activity coefficient for water ( we apply the Aerosol Inorganic Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model (validated at room temperatures; Zuend et al., 2008, 2011). The reference state for ions and water in the model is an infinitely dilute aqueous solution ( and .
For relatively dilute HSO solutions (low solute concentration), typical for most atmospheric conditions, it is reasonable to assume that the dissociation of HSO to HSO (Reaction R1) is complete (Clegg et al., 1998; Zuend et al., 2008). However, in this work we demonstrate that this assumption fails at low RH and also for small particles with a large Kelvin term. Furthermore, at a very low water activity ( (less than 0.01) a non-negligible fraction of the HSO could potentially decompose to SO (Reaction R3); if this is the case, the thermodynamic model need to consider not only Reaction (R1) but (R3) as well (Fig. 1).
Since AIOMFAC does not consider inorganic non-electrolyte compounds like HSO and SO we implement additionally to this the symmetric electrolyte-NonRandom Two-Liquid (eNRTL) activity coefficient model (Bollas et al., 2008; Song and Chen, 2009) which is optimised for the HSO–HO–SO systems by Que et al. (2011). In this work we use the regressed eNRTL binary interaction parameters from Que et al. (2011). Following the convention of the eNRTL model (Chen et al., 1982), we set the unknown binary parameters for NH–molecule, molecule–NH and NH–ions to 4, 8 and 0, respectively.
The reference state of the molecular species in eNRTL is defined as the pure liquid. eNRTL provides mole-fraction-based activity coefficients for HSO and SO, and , respectively. ADCHAM calculates and as a function of and N : S, : (Fig. S3). The modelled and approach unity not only at the standard state of the pure liquids ( and ), but also for the infinitely dilute aqueous solution ( and ). This is because the eNRTL binary HO–HSO and HO–SO interaction parameters are zero in the model. For all conditions between these limiting states, the short-range ion (HSO, SO, NH, H–molecule (HSO, SO interactions, and Pitzer–Debye–Hückel long-range ion–molecule interactions influence the modelled and . At K, reaches the highest values ( 2.29) when and reaches the highest values ( 1.95) when 0.35 (Fig. S3). We also assume that the activity coefficient of NH is unity for the model simulations. However, sensitivity tests performed for 0.1 and reveal that, for the acidic particles (N : S 1), our model results are completely insensitive of the absolute value of .
The particle-phase composition
If ammonium cation (NH is present in the sulfuric acid particles, then solid ammonium bisulfate (NHHSO(s)) may form when the S(VI) and HO start to evaporate from the particles. However, the particles may also stay as highly supersaturated droplets with respect to the crystalline phase (Zuend et al., 2011). The particle number size distribution measurements in our experiments do not indicate a sudden drop in particle size during evaporation. This is expected when the particles crystalise and all particle water is suddenly removed. Thus, in the present work we do not consider formation of any solid salts. We further neglect the influence of any mass-transfer limitations in the particle phase, and assume that the particle ion-molecule equilibrium composition (Reactions R1–R3) and water content can be modelled as equilibrium processes (because they are established rapidly compared to the composition change induced by the evaporation of HSO and SO. We use the thermodynamic model to update the particle equilibrium water content, mole fractions and activity coefficients of all species. Then the model considers the gas–particle partitioning of HSO and SO with a condensation algorithm in the aerosol dynamics model (Sect. 3.3.5). The time step set in the model is 1 s.
The thermodynamic model uses an iterative approach to calculate the particle equilibrium mole fractions of HO, HSO SO, HSO, SO, NH, NH and H, based on the current time step, known RH, and absolute number of moles of S(VI) and N(-III) for each particle size bin. The modelled particle-phase mole fraction of N(-III) during the evaporation experiments is always substantially lower than that of S(VI) (N : S 0.7). For these particles the saturation vapour pressure of NH is always less than 10 Pa, within the experimental water activity range 0–0.11 and . Thus, it is reasonable to assume that during the experiments NH does not evaporate from the particles.
Based on the particle diameters from the previous time step (which depend on the particle water content), the thermodynamic model starts by calculating for each particle size, considering the Kelvin effect. Given , the model estimates the particle water mole fraction. Then the model calculates the H molality in the aqueous phase via a fourth-order polynomial, derived from the ion balance equation, Eq. (2), in combination with the thermodynamic equilibrium constant equations, Eqs. (3)–(6), and the S(VI) and N(-III) mole balance equations, Eqs. (7) and (8), respectively. The maximum positive real root of this polynomial gives the H concentration, [H]. The thermodynamic equilibrium coefficients for HSO and HSO dissociations and NH protonation (Eqs. 3, 4 and 6) are given in a molality-based form while the equilibrium coefficient in Eq. (5), which involves the equilibration between the different solvents (HO, SO and HSO, is given in a mole-fraction-based form. The Eq. (5) is given in a mole-fraction-based form for the following reasons: (a) the eNRTL provides mole-fraction-based activity coefficients, and (b) if Eq. (5) were to be applied for that are even lower than considered in this work, the assumption of using molalities, i.e. where water is considered to be the only solvent, would not be acceptable. The model calculates and (mol kg with Eqs. (9) and (10) (Jacobson, 2005). We treat and as unknown model fitting parameters. Once [H] is determined, all other ion and molecule concentrations can be derived from Eqs. (2)–(8). Based on the new estimated particle-phase ion and molecule mole fractions, the thermodynamic model uses AIOMFAC and eNRTL to update the ion and molecule activity coefficients. The model then repeats the whole procedure iteratively until the relative change in the concentration and activity coefficients for each compound is less than 10 between successive iteration steps. To stabilise convergence, the model estimates activity coefficients used in the proceeding iteration as a weighted average of the values from the previous and present iteration time steps.
HSO and SO in the gas phase
In the gas phase only a fraction of HSO is in the form of pure sulfuric acid molecules while the rest of the HSO is in a hydrated form. In this work we use the parameterisation from Hanson and Eisele (2000), who measured the diffusion loss rate of HSO to flow-tube walls at different RH, to estimate the RH-dependent effective diffusion coefficient of HSO.
In the gas phase, SO reacts rapidly with HO to form HSO. Based on the measured loss rate of SO, which shows a second-order dependence on the water vapour concentration (Jayne et al., 1997), we estimate that SO(g) is converted to HSO in less than 1 s during the CLOUD chamber experiments, even at the lowest RH. Because of this rapid conversion to HSO and the high vapour pressure of SO (Eq. 12), it is reasonable to assume that the gas-phase concentration of SO (vapour pressure, is negligibly low.
Saturation vapour pressures, surface tension and particle density
We use Eqs. (11) and (12) to calculate the temperature-dependent sub-cooled pure-liquid saturation vapour pressures for HSO and SO (, where refers to HSO or SO in Pa). Equation (11) is based on the work of Ayers et al. (1980), with corrections for lower temperatures by Kulmala and Laaksonen (1990). We use the (best fit) parameter value of 11.695 (Noppel et al., 2002, Noppel–Kulmala–Laaksonen, N–K–L, parameterisation; see Supplement Fig. S5a). Equation (12) is based on the work of Nickless (1968) (see Supplement Fig. S5b). As an alternative to Eqs. (11) and (12) we also use the HSO and SO pure-liquid saturation vapour pressure parameterisations from Que et al. (2011) (originally from the Aspen Plus Databank, Fig. S5).
We calculate the saturation vapour pressures of HSO and SO for each particle size with Eq. (13), using the mole fractions ( and mole-fraction-based activity coefficients ( of HSO and SO (from the thermodynamic model) and the Kelvin term, Eq. (14) for compound in particle size bin . where is the activity of compound in size bin , is the temperature in kelvin, is the universal gas constant (J mol K, is the molar mass (kg mol of compound is the density (kg m of the liquid particles, is the surface tension (N m and is the diameter (m) of the particles in size bin .
As an alternative approach we also model the evaporation of HSO using composition-dependent HSO activities derived directly from the tabulated values of the difference in chemical potentials between the sulphuric acid in aqueous solution and that of the pure acid . The tabulated values that are valid at 298.15 K are taken from Giauque et al. (1960). The relationship between and is given by Eq. (15). In accordance with Ayers et al. (1980) we neglect any temperature dependence of . This empirically based approach is used in several chemistry transport models to simulate the evaporation of pure sulfuric acid particle in the stratosphere (see, e.g., Kokkola et al., 2009; English et al., 2011; Hommel et al., 2011).
We calculate the surface tension and density of the particles comprising a ternary mixture of water, sulfuric acid and ammonium with parameterisations given by Hyvärinen et al. (2005) that combine surface tension parameterisations for (NHSO–HO mixtures (Hämeri et al., 2000; Korhonen et al., 1998b), HSO–HO mixtures (Vehkamäki et al., 2002) and NH–HO mixtures (King et al., 1930). For the range of conditions in our experiments the minimum particle diameter after evaporation is 50 (10) nm (for experiments 1 and 2). The Kelvin effect only increases the water saturation vapour pressure by maximum value of 1.07 (and the HSO saturation vapour pressure by 1.44; see Supplement Fig. S6) for the particle diameter of 40 nm.
Evaporation of HSO, SO and HO
We model the gas-particle partitioning (evaporation) of HSO and SO using the full moving size distribution method in combination with the Analytic Prediction of Condensation (APC) scheme (Jacobson, 2005). APC is an unconditionally stable numerical discretisation scheme used to solve the condensation equation, Eq. (16). In Eq. (16), we substitute the saturation vapour pressures from Eq. (13) and the measured concentration, (vapour pressure, of HSO. Based on the motivation given in Sect. 3.3.3 the vapour pressure of SO, , is set to zero.
Equation (16) describes the contribution of species to the mass growth rate of a particle in size bin , is the Fuchs–Sutugin correction factor in the transition region (Fuchs and Sutugin, 1971), , correspond to diameters (m) and , to diffusion coefficients (m s of the condensing molecule and the particles in size bin , respectively. is the mass-accommodation coefficient of compound and is the non-dimensional Knudsen number, Eq. (17). is the mean free path (m) and and are the thermal speeds (m s of the molecule and the particles in size bin , respectively. Equations (16) and (17) take into account that the condensing molecules have a non-negligible size compared to the size of the smallest particles, and that small particles have non-negligible diffusion coefficients (Lehtinen and Kulmala, 2003).
Based on measurements of HSO losses in a flow tube reactor, Pöschl et al. (1998) derived a mass accommodation coefficient of HSO on aqueous sulfuric acid, which was close to unity, with a best fit value of 0.65, a lower limit value of 0.43 and an upper limit of 1.38 (physical limit 1.0). The measured mass accommodation coefficients do not show any dependence on the relative amount of water in the particles (Pöschl et al., 1998). For the model simulations in this work we use unity mass accommodation coefficients. The particle water content is modelled as an equilibrium process with the thermodynamic model (see Sect. 3.3.2).
Particle losses
The electric field strength of the stainless-steel CLOUD chamber, in contrast to smog chambers made of Teflon, is very low. Therefore, we can neglect electrostatic deposition enhancements (for details on how ADCHAM treats particle wall deposition losses see Roldin et al., 2014). We simulate the particle-size-dependent deposition losses with the model from Lai and Nazaroff (2000). The particle deposition loss depends on the friction velocity (, which we treat as an unknown model fitting parameter. The best possible agreement between the modelled and measured particle number and volume concentration in the chamber is achieved with a friction velocity of 0.2 m s. Thus, for all model results we present in this article we use 0.2 m s. Dilution losses due to the purified air injected to the CLOUD chamber are also considered in the model.
Constraining the thermodynamic properties of sulfate aerosol particles
We use ADCHAM to constrain the values of the thermodynamic equilibrium coefficients, and , by treating these coefficients as unknown model fitting parameters. By varying the equilibrium coefficients we search for the best possible agreement (coefficient of determination (; see Supplement, Table S1) between the modelled and measured geometric mean diameter (GMD) with respect to particle number. Because experimental results reveal that the sulfate particles did not evaporate completely, they must have been contaminated with a small fraction of effectively non-volatile material (Sect. 3.2).
In the model we address this by assuming either that the particles (prior to evaporation) contained a small fraction of non-volatile organic material (e.g. secondary organic aerosol, SOA) or that the particles contained small amounts of ammonium, which prevented pure HSO particle formation and consequently prevented the evaporation. We calculate the initial SOA and ammonium dry particle volume fraction in particle size bin ( and with Eqs. (19) and (20), respectively. Here and represent an effective particle diameter of SOA and ammonium if all other particle species are removed. For experiment 1 we use nm and nm, for experiment 2 nm and nm and for experiment 3 nm and nm.
Results and discussion
In order to fit the modelled particle number size distribution evolution to the observations we performed several hundred simulations where we varied and . We summarise these simulations into three main categories (cases):
Case 1: only HSO and HO evaporation (.
Case 2: a combination of HSO, HO and SO evaporation.
Case 3: practically only SO and HO evaporation.
Particle-phase mole fractions
Modelled particle-phase mole fractions of (a) HSO, , and (b) SO, , as a function of the water activity ( and the N : S for Case 2a which represents the combination of HSO, HO and SOevaporating species with HSO being the dominating evaporating S(VI) species. The colour-coded contours on the – axes represent constant particle-phase mole fractions for (a) –6 10 and (b) .3–1.8 10. The equilibrium coefficients are .40 10 mol kg, and .43 10 at .8 K.
[Figure omitted. See PDF]
Figure 2 shows an example of the modelled mole fractions of (a) HSO, , and (b) SO, , as a function of the and N : S for Case 2a with equilibrium constants 10 mol kg, and 1.43 10 at .8 K. Figure 2 reveals that the increase in as decreases is steeper than for . This is because HSO formation precedes SO formation (see Reaction R3). As expected, the highest values of and occur when N : S and approaches zero. While N : S increases, and decrease gradually and reach lower values when N : S becomes larger than 0.6.
Particle number size distribution evolution
Particle shrinkage at low RH. Measured (a) and modelled (b) particle number size distribution evolution during experiment 2 performed at .8 K for Case 2a, with HSO being the dominating evaporating S(VI) species, .40 10 mol kg and .43 10. Panels (c) and (d) show the modelled particle water mole fraction, and N : S, respectively.
[Figure omitted. See PDF]
In Fig. 3 we present the particle number size distribution evolution after the shutter of the UV light is closed and the influx of water vapour to the chamber is interrupted for experiment 2, performed at .8 K, showing (a) the measured and (b) the modelled values for Case 2a with 10 mol kg and .43 10. At the beginning of the evaporation process the particles in the size range from 60 to 180 nm in diameter contain approximately 70 mole % HO; however, this percentage decreases, declining to 15 mole % after 6 h (Fig. 3c). Before HSO and SO start to evaporate from the particles the assumed mole fraction of ammonium is very low (Fig. 3d). However, during the evaporation process N : S increases steadily until it reaches a value of 0.6 after 6 h. At this point the particles are 40 nm in diameter and do not shrink further. This model result is in good agreement with the experimental results reported by Marti et al. (1997) and confirms that NH effectively stabilises sulfur particles against evaporation when N : S 0.6. Thus, in the stratosphere, even small amounts of a base (such as NH can prevent the sulphate particles from shrinking.
Geometric mean diameter shrinkage influenced by relative humidity
Measured and modelled GMD evolution as a function of (a) time and (b) RH for experiments 1 and 2 performed at .8 K. The modelled particles are composed of S(VI), HO and NH as a particle-phase contaminant. The simulations correspond to Case 1 with HSO being the only evaporating S(VI) species, .00 10 mol kg; Case 2a with HSO being the dominating evaporating S(VI) species, .40 10 mol kg and .43 10; Case 2b with SO being the dominating evaporating S(VI) species, .00 10mol kg and .54 10; and Case 3 with SO being the only evaporating S(VI) species, .00 10 mol kg and .33 10 (see Supplement, Table S1, simulations 1–4 and 13–16). The pure-liquid saturation vapour pressures of HSO and SO are calculated with Eq. (11), N–K–L parameterisation (Kulmala and Laaksonen, 1990; Noppel et al., 2002), and Eq. (12) (Nickless, 1968), respectively.
[Figure omitted. See PDF]
Figure 4 compares the measured and modelled GMD evolution as a function of (a) time and (b) RH for experiments 1 and 2 performed at a temperature of 288.8 K (Table 1) with NH as a particle-phase contaminant (see Supplement, Table S1, simulations 1–4 and 13–16). The pure-liquid saturation vapour pressures of HSO and SO are calculated with Eqs. (11) and (12). The model results are in good agreement with the measured GMD trend for Case 1 (.00 10 mol kg, Case 2a (.40 10 mol kg and .43 10, Case 2b (.00 10 mol kg and .54 10 and Case 3 (.00 10 mol kg and .33 10. The Case 3 simulations give a particle shrinkage that begins somewhat too late and occurs somewhat too rapidly. However, considering the measurement uncertainties it is impossible to constrain the relative contribution of HSO and SO to the observed GMD loss only based on these two experiments (see Sect. 4.4).
With the Aspen Plus Databank pure-liquid saturation vapour pressure parameterisations it is also possible to find similarly good agreement between the modelled and observed GMD evolution during experiment 1 and 2 for cases 1, 2a, 2b and 3 (Fig. S8) with NH as the particle-phase contaminant, but with somewhat different values of and (see Supplement, Table S1, simulations 8–11 and 20–23).
The model simulations with non-volatile and non-water-soluble organics or dimethylamine (DMA) as the particle-phase contaminant give nearly identical results to those with NH, both for experiments 1 and 2 (see Supplement Table S1, simulations 6, 7, 17 and 18). In the case of DMA this occurs because it is also a strong enough base to be completely protonated (all N(-III) is in the form of NH. In the case of an organic contaminant instead of NH the model results mainly differ at a later stage of the particle evaporation phase when the N : S approaches 0.5. This is because the evaporation rate does not slow down before all S(VI) is lost when the particles do not contain any base (see Fig. S9). Thus, the modelled GMD shrinkage becomes somewhat faster when assuming organic contamination. Without any particle-phase contamination (pure sulfuric acid particles) the particles evaporate faster and completely (see Supplement, Fig. S10).
Instead of explicitly calculating the HSO activity with the thermodynamic model we derive it directly from the tabulated values of the HSO chemical potentials as a function of the molality, following Giauque et al. (1960), Eq. (15). With this method we simulate the evaporation of HSO without explicitly calculating the concentration of HSO in the particles. However, since the tabulated chemical potentials from Giauque et al. (1960) are only valid for pure sulfuric acid solutions and temperatures close to 298.15 K, it cannot be used if the particle aqueous phase also contains ammonium or other stabilising molecules.
Based on data from Giauque et al. (1960), Eq. (15) and the pure-liquid saturation vapour pressure parameterisation, Eq. (11) (N–K–L parameterisation), the modelled GMD shrinkage is consistent with the observations for experiments 1 and 2 when we consider the Case 1 (HSO as the only evaporating S(VI) species) and particle-phase contamination due to non-volatile non-water-soluble organics (see Supplement, Fig. S11 and Table S1, simulations 5, 12, 19 and 24). However, when we use the pure-liquid saturation vapour pressure parameterisation from the Aspen Plus Databank, the modelled particles evaporate earlier (at higher RH) than the observed particles. The reason is that the ASPEN compared to N–K–L parameterisation gives higher saturation vapour pressures (see Supplement, Fig. S5).
Geometric mean diameter shrinkage influenced by relative humidity and temperature
In an attempt to constrain how and depend on the temperature, and the role of HSO and SO on the observed particle diameter shrinkage, as a next step we simulate experiment 3, which expands in temperature. For this experiment the temperature increases gradually from 268 to 293 K, while the absolute humidity remains at a constant value, thus allowing the RH to decrease. Equation (21) describes the modelled temperature dependence of and , where the values at .8 K ( set equal to the values in regard to the model simulations of experiments 1 and 2 (Sect. 4.3): where can be either HSO or SO. With K there is no temperature dependence of .
For other acids like HNO, HCl and HSO, decreases with increasing () (Jacobson, 2005). Que et al. (2011) estimate to be 3475 K and to be 14 245.7 K. Thus, based on this information we would expect the equilibrium Reactions (R1) and (R3) to shift towards the left (more HSO and SO as temperature increases). This would result in a stronger temperature dependence of the HSO and SO saturation vapour pressures over aqueous sulfuric acid droplets (Eq. 13) compared to the temperature dependence expected if we only consider the temperature effect of the pure-liquid saturation vapour pressures (Fig. S5).
Measured and modelled GMD evolution as a function of (a) time and (b) RH for experiment 3 performed at a temperature range from 268 to 293 K. The modelled particles are composed of S(VI), HO and either NH or non-volatile, non-water-soluble organics as a particle-phase contaminant. The simulations correspond to Case 1 (the HSO activity is calculated with use of Eq. (15) and the tabulated HSO chemical potentials from Giauque et al., 1960; see Supplement, Table S1, simulation 28) and Case 2a, .40 10 mol kg and 1.43 10 at 288.8 K (see Supplement, Table S1, simulations 29, 33, 34 and 36). The pure-liquid saturation vapour pressures of HSO and SO are calculated with Eq. (11) (Kulmala and Laaksonen, 1990; Noppel et al., 2002) and Eq. (12) (Nickless, 1968), respectively.
[Figure omitted. See PDF]
Figure 5 compares the measured and modelled GMD evolution during experiment 3. For the simulations we use either the same temperature dependence as suggested by Que et al. (2011) ( K and 245.7 K) or no temperature dependence of and K and 0 K) or weak temperature dependence K and 3000 K. One of these model simulations corresponds to Case 1 and the rest to Case 2a (see Supplement, Table S1, simulation 28 and 29, 33, 34 and 36, respectively).
For the Case 1 simulation (see Supplement, Table S1, simulation 28) we use Eq. (15) and the tabulated HSO chemical potentials from Giauque et al. (1960) to derive the HSO activity. The particle-phase contaminant is assumed to be non-volatile and non-water-soluble organics. In this simulation the modelled particles grow somewhat too much before they start to shrink. For the Case 2a simulation, where the temperature dependences of and are described by the and values derived by Que et al. (2011) (see Supplement, Table S1, simulation 29), the model cannot capture the observed GMD evolution. For the Case 2a simulations with K and K (see Supplement, Table S1, simulations 33 and 34) the particle-phase contaminant is assumed to be NH or non-volatile and non-water-soluble organics. These model simulations, which agree with the observed GMD, indicate that the temperature dependences of and need to be very weak or insignificant ( K and K). If the particles are contaminated with NH, or even needs to be negative for optimum fitting (e.g. K and 3000 K; see Supplement, Table S1, simulations 36). It is also possible to find good agreement between the modelled and measured GMD evolution if one of and is negative and the other one is positive ( 3475 K and 10 000 K; see Supplement, Table S1, simulation 31). The HSO and SO pure-liquid saturation vapour pressures in these simulations are calculated with Eqs. (11) and (12).
If we instead use the pure-liquid saturation vapour pressure parameterisations from the Aspen Plus Databank (which have somewhat weaker temperature dependences than Eqs. 11 and 12), the model results captures the observed GMD evolution if both and are zero and HSO is the only evaporating (SVI) species (Case 1; see Supplement, Table S1, simulation 50) or the main evaporating S(VI) species (Case 2a; see Supplement, Table S1, simulation 51; see Supplement, Fig. S12).
For Case 2b and 3 simulations in which we assume that SO is responsible for most of the S(VI) evaporation, the model can never capture the observed GMD evolution. This is the case regardless of the pure-liquid saturation vapour pressure method we use (N–K–L–Nickless or Aspen Plus Databank; see Supplement, Table S1, simulations 42, 48, 52 and 53).
Based on the simulations of experiment 3 we conclude that most of the S(VI) that evaporated from the particles probably was in the form of HSO (cases 1 and 2a). The very weak temperature dependences for and needed for the model to capture the GMD evolution during experiment 3 is surprising and calls for further investigation. Part of the explanation to this could be that the AIOMFAC activity coefficient model is developed based on experimental data derived at 298.15 K. The uncertainty arising from the two different pure-liquid saturation vapour pressure parameterisations (temperature-dependent) also limits our ability to fully constrain the and values. Based on our experiments and model simulations the equilibrium constant should be somewhere in the range 2.0–4.0 10 mol kg and the needs to be larger than 1.4 10 at a temperature of 288.8 5 K. The type of contamination of the sulfate particles (NH, DMA or a non-volatile non-water-soluble organic compound) does not have a substantial impact on our results and conclusions.
Atmospheric implications
In the following section, we define an effective saturation concentration of HSO as the sum of the saturation concentration of HSO and SO, based on the assumption of rapid conversion of SO to HSO, Eq. (22) (see Supplement S5, Fig. S7). Figure 6 shows the modelled effective HSO saturation concentration as a function of particle size (–10 nm) and RH (0–100 %). The results are from a model simulation with 2.40 10 mol kg and 1.43 10, 8 K and pure-liquid saturation vapour pressures calculated with Eqs. (11) and (12). The four different panels (a–d) correspond to simulations using four different values for N : S, namely 0, 0.5, 0.75 and 1. In each panel, the contours show the levels. For example, the contour corresponds to an effective HSO saturation concentration of 10 molecules cm. These contours provide the HSO gas-phase concentration at which the net flux of S(VI) to and from the particles is zero (particles neither grow nor shrink).
Modelled effective HSO saturation concentration, (molecules cm, expressed in , at .8 K, RH 0–100 % and particle diameters in the range from 1 to 10 nm. The contours represent HSO gas-phase concentrations, e.g. 7 corresponds to molecules cm. The grey shading indicates the atmospheric range of HSO (10 cm. The results correspond to particles composed (a) only of S(VI) and HO (N : S ), (b) with N : S 0.5, (c) with N : S 0.75 and (d) with N : S . The equilibrium constants are 2.40 10 mol kg and 1.43 10. The pure-liquid saturation vapour pressures of HSO and SO are calculated with Eqs. (11) and (12).
[Figure omitted. See PDF]
The observed atmospheric daytime range of the [HSO] is approximately 10–10 molecules cm, and so we shade this range in Fig. 6. When is less than this range (to the upper right in the panel), the particles for most atmospheric daytime conditions will grow by condensation of HSO; when is greater than this (to the lower left in the panel) the particles will for most conditions shrink by evaporation of S(VI); in the shaded range the particles will tend to equilibrate. The larger the mole fraction of bases (NH in the aerosol particles the less prone they will be to shrink. When particles are composed only of S(VI) and HO (N : S ) and the concentration of HSO is 10 molecules cm all particles smaller than 10 nm will shrink at RH 13.2 %. For the same [HSO] and N : S 0.5 all particles smaller than 10 nm shrink at RH 12.1 %. However, for N : S 0.75 particles smaller than 4 nm shrink at RH 5.5 %, and if N : S 1 only particles smaller than 1.9 nm shrink, independent of RH except when it is extremely dry (RH 1.5 %). With the vapour pressure parameterisations from the Aspen Plus Databank and 4.00 10 and .55 10 the results are almost identical.
These model results demonstrate that sulfuric acid can evaporate from particles or be unable to contribute to their growth for atmospherically relevant conditions, characterised by low relative humility, relatively high temperatures and weak sources of NH and SO. Such environments can be found in the stratosphere and possibly also in the troposphere over large desert regions.
Summary and conclusions
This study demonstrates, both experimentally and theoretically, the importance of HSO evaporation from aerosol particles at atmospheric relevant conditions. We measured the sulfate aerosol particle shrinkage below a certain low relative humidity (e.g. RH 1.5 % for .8 K and RH 0.7 % for .0 K) in the CLOUD chamber at CERN. We modelled the sulfur evaporation with ADCHAM. Our model simulation showed the following:
- i.
The dissociation of HSO is not complete, and evaporation of HSO and HO can explain the observed particle shrinkage. However, we cannot dismiss the possibility that some of the shrinkage is due to evaporating SO, which is formed when HSO is dehydrated.
- ii.
The equilibrium rate coefficient for the first dissociation stage of HSO ( falls somewhere in the range 2.0–4.0 10 mol kg at 288.8 5 K.
- iii.
The equilibrium coefficient for the dehydration of HSO ( must at least be larger than 1.4 10.
The main factors limiting our estimation of are uncertainties in the pure-liquid saturation vapour pressure of HSO and the relative contribution of SO to the observed particle evaporation. Other potential sources of error are the uncertainties in the derived activity coefficients, the mass accommodation coefficient of HSO and solid salt formation during the particle evaporation phase. The model simulations of an experiment where the temperature was gradually increased from 268 to 293 K indicate that the temperature dependencies of and need to be weak. Future studies should focus on constraining the pure-liquid saturation vapour pressures of HSO and SO and the temperature dependence of and .
In order to be able to make an accurate prediction of the sulfate particles' influence on global climate, their thermodynamic properties need to be properly described in global climate models. Thus, our constraints on the dissociation, and dehydration, of HSO are important contributions to the global aerosol–climate model community. The outcome of this study implies that atmospheric modelling studies, especially those dedicated to new-particle formation, should not by default assume that sulfate particles are non-volatile. Models that exclude the evaporation process provide faster particle formation rates which has a misleading effect on the impact of aerosols on climate.
Our results are especially meaningful for high-altitude new-particle formation (e.g. in the upper troposphere and stratosphere). It has been previously reported that the particle formation (Brock et al., 1995) and the ion-induced nucleation (Lee et al., 2003; English et al., 2011) are sources of new particles in high altitudes. In the upper troposphere and stratosphere general circulation models coupled with aerosol dynamics models use aerosol evaporation as a source of [HSO] (English et al., 2011). The concentration of HSO drastically affects new-particle formation rates. The equilibrium constants for the dissociation and dehydration of HSO reported in this study are needed to accurately model the sulfate aerosol particle evaporation and concentration of HSO. They may also be important to evaluate particle formation schemes (homogeneous, ion-induced) for stratospheric conditions. These schemes are generally constrained based on tropospheric conditions (English et al., 2011) but applied for stratosphere simulations. Moreover, vapour-phase HSO in the atmosphere appears to be ubiquitous, even in the absence of photochemistry (Mauldin et al., 2003; Wang et al., 2013); this may partly be due to evaporation of HSO from aerosol particles.
In a changing climate it will become even more important to understand the thermodynamic properties of the sulfur aerosol particles involved in the development of polar stratospheric clouds and how sulfate aerosols influence the stratospheric O layer. Experiments simulating stratospheric conditions (–265 K, 10–10 atm, RH 1.0 % and [HSO molec. cm are of great importance. Our results may also assist in explaining the atmospheric sulfur cycle of Venus. The Venusian clouds that are made up largely of sulfuric acid droplets cover an extended temperature range from 260 K (upper clouds) to 310 K (middle clouds) and even higher (lower clouds). The scientific understanding of the upper tropospheric and stratospheric sulfate aerosol is of great importance for the global climate and requires further investigation.
Requests for underlying material should be addressed to the corresponding author, Georgios Tsagkogeorgas ([email protected]).
The Supplement related to this article is available online at
GT and JD designed and performed the experiments. GT, JD and PR analysed the data. PR developed the model code. PR and GT performed the simulations. GT, JD, LR, JT, JGS, and AK collected the data and contributed to the analysis. GT, PR, JD, and NMD assisted in drafting the manuscript. GT, PR, JD, MB, JC, RCF, MK, NMD and FS contributed to scientific interpretation and editing of the manuscript. All authors contributed to the development of the CLOUD facility and analysis instruments and commented on the manuscript.
The authors declare that they have no conflict of interest.
Acknowledgements
We would like to thank CERN for supporting CLOUD with important technical and financial resources, and for providing a particle beam from the CERN Proton Synchrotron. We also thankPatrick Carrie, Louis-Philippe De Menezes, Jonathan Dumollard, Roberto Guida, Katja Ivanova, Francisco Josa, llia Krasin, Robert Kristic, Abdelmajid Laassiri, Osman Maksumov, Serge Mathot, Benjamin Marichy, Herve Martinati, Antti Onnela, Robert Sitals, Hansueli Walther, Albin Wasem and Mats Wilhelmsson for their important contributions to the experiment. This research has received funding from the EC Seventh Framework Programme (Marie Curie Initial Training Network “CLOUD-ITN” no. 215072 and “CLOUD-TRAIN” no. 316662, ERC-Starting “MOCAPAF” grant no. 57360 and ERC-Advanced “ATMNUCLE” grant no. 227463), the German Federal Ministry of Education and Research (project nos. 01LK0902A and 01LK1222A), the Swiss National Science Foundation (project nos. 200020 135307 and 206620 141278), the Academy of Finland (Centre of Excellence project no. 1118615 and other projects: 135054, 133872, 251427, 139656, 139995, 137749, 141217, 141451), the Finnish Funding Agency for Technology and Innovation, the Vaisala Foundation, the Nessling Foundation, the Austrian Science Fund (FWF; project no. J3198-N21), the Portuguese Foundation for Science and Technology (project no. CERN/FP/116387/2010), the Swedish Research Council, Vetenskapsradet (grant 2011-5120), the Presidium of the Russian Academy of Sciences and Russian Foundation for Basic Research (grants 08-02-91006-CERN and 12-02-91522-CERN), the US National Science Foundation (grants AGS1136479, AGS1447056, AGC1439551 and CHE1012293), the PEGASOS project funded by the European Commission under the Seventh Framework Programme (FP7-ENV-2010-265148), and the Davidow Foundation. We thank the tofTools team for providing tools for mass spectrometry analysis.
Pontus Roldin would like to thank the Cryosphere-Atmosphere Interactions in a Changing Arctic Climate (CRAICC) Nordic Top-Level Research Initiative and the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning FORMAS (project no. 214-2014-1445) for financial support.Edited by: Yafang Cheng Reviewed by: two anonymous referees
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
© 2017. This work is published under https://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Abstract
Evaporation of sulfuric acid from particles can be important in the atmospheres of Earth and Venus. However, the equilibrium constant for the dissociation of H
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details








1 Leibniz Institute for Tropospheric Research, 04318 Leipzig, Germany
2 Department of Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland; Division of Nuclear Physics, Lund University, P.O. Box 118, 221 00 Lund, Sweden
3 Department of Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland; Helsinki Institute of Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
4 Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
5 Paul Scherrer Institute, 5232 Villigen, Switzerland
6 Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany; now at: Atmospheric Chemistry Department, Max Planck Institute for Chemistry, 55128 Mainz, Germany
7 Department of Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
8 Fac. Ciencias & CENTRA, Universidade de Lisboa, Campo Grande, 1749–016 Lisbon, Portugal
9 Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany; CERN, 1211 Geneva, Switzerland
10 California Institute of Technology, Pasadena, CA 91125, USA
11 Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15213, USA